Greg Wayne
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Artificial Intelligence top 2%
- Reinforcement Learning in Robotics
- Topic Modeling
- Neural Networks and Applications
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Reservoir Computing
Papers in ⓘ
-
- Neural dynamics and brain function 4
- EEG and Brain-Computer Interfaces 2
-
- Neural Networks and Applications 2
- Reinforcement Learning in Robotics 2
- Co-authors
- Konrad P. Körding (2 shared papers)Adam Marblestone (2 shared papers)Ivo Danihelka (4 shared papers)Alex Graves (4 shared papers)Josh Merel (5 shared papers)Matthew Botvinick (2 shared papers)Tim Harley (2 shared papers)Edward Grefenstette (1 shared paper)
- Journals
- Nature (2 papers)ACM Transactions on Graphics (1 paper)Nature Communications (1 paper)Nature Neuroscience (1 paper)Neural Computation (1 paper)
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Greg Wayne
16 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Cognitive Neuroscience 495
- Artificial Intelligence 810
- Computer Vision and Pattern Recognition 339
- Neurology 76
- Sensory Systems 43
Countries citing papers authored by Greg Wayne
This map shows the geographic impact of Greg Wayne's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Greg Wayne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg Wayne more than expected).
Fields of papers citing papers by Greg Wayne
This network shows the impact of papers produced by Greg Wayne. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Greg Wayne. The network helps show where Greg Wayne may publish in the future.
Co-authors
The 25 scholars most cited alongside Greg Wayne, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Hybrid computing using a neural network with dynamic external memory Hit paper breakdown → | 2016 | 683 |
| 2 | Toward an Integration of Deep Learning and Neuroscience Hit paper breakdown → | 2016 | 353 |
| 3 | 2019 | 140 | |
| 4 | 2014 | 115 | |
| 5 | Learning continuous control policies by stochastic value gradients | 2015 | 113 |
| 6 | 2020 | 59 | |
| 7 | 2014 | 54 | |
| 8 | 2016 | 52 | |
| 9 | 2023 | 28 | |
| 10 | Robust imitation of diverse behaviors | 2017 | 25 |
| 11 | 2016 | 25 | |
| 12 | 2024 | 20 | |
| 13 | 2016 | 15 | |
| 14 | Hierarchical Visuomotor Control of Humanoids. | 2018 | 9 |
| 15 | 2014 | 5 | |
| 16 | 2011 | 5 |
About Greg Wayne
Greg Wayne is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Control and Systems Engineering, Sensory Systems and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 1.7k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Robot Manipulation and Learning (4 papers), Neural dynamics and brain function (4 papers), Ferroelectric and Negative Capacitance Devices (2 papers), EEG and Brain-Computer Interfaces (2 papers), Neural Networks and Applications (2 papers), Human Pose and Action Recognition (2 papers) and Reinforcement Learning in Robotics (2 papers). The work is most often cited by research in Cognitive Neuroscience (495 citations), Artificial Intelligence (810 citations), Computer Vision and Pattern Recognition (339 citations), Neurology (76 citations) and Sensory Systems (43 citations). Greg Wayne has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Konrad P. Körding, Adam Marblestone, Ivo Danihelka, Alex Graves, Josh Merel, Matthew Botvinick, Tim Harley, Edward Grefenstette, Tiago Ramalho and John Agapiou. Their work appears in journals such as Nature, ACM Transactions on Graphics, Nature Communications, Nature Neuroscience and Neural Computation.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.